ON-LINE VOLTAGE STABILITY EVALUATION USING NEURO-FUZZY INFERENCE SYSTEM AND MOTH-FLAME OPTIMIZATION ALGORITHM

Authors

  • Arif Bourzami University of Ferhat Abbes Setif, Algeria
  • Mohammed Amroune University of Ferhat Abbes Setif, Algeria
  • Tarek Bouktir University of Ferhat Abbes Setif, Algeria https://orcid.org/0000-0001-6352-2146

DOI:

https://doi.org/10.20998/2074-272X.2019.2.07

Keywords:

voltage stability, line voltage stability index, Moth-Flame optimization, adaptive neuro-fuzzy inference system

Abstract

Purpose. In recent years, the problem of voltage instability has received special attention from many utilities and researchers. The present paper deals with the on-line evaluation of voltage stability in power system using Adaptive Neuro-Fuzzy Inference System (ANFIS). The developed ANFIS model takes the voltage magnitudes and their phases obtained from the weak buses in the system as input variables. The weak buses identification is formulated as an optimization problem considering the operating cost, the real power losses and the voltage stability index. The recently developed Moth-Flame Optimization (MFO) algorithm was adapted to solve this optimization problem. The validation of the proposed on-line voltage stability assessment approach was carried out on IEEE 30-bus and IEEE 118-bus test systems. The obtained results show that the proposed approach can achieve a higher accuracy compared to the Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks.

Author Biographies

Arif Bourzami, University of Ferhat Abbes Setif

Department of Electrical Engineering

Mohammed Amroune, University of Ferhat Abbes Setif

Department of Electrical Engineering

Tarek Bouktir, University of Ferhat Abbes Setif

Department of Electrical Engineering

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Published

2019-04-16

How to Cite

Bourzami, A., Amroune, M., & Bouktir, T. (2019). ON-LINE VOLTAGE STABILITY EVALUATION USING NEURO-FUZZY INFERENCE SYSTEM AND MOTH-FLAME OPTIMIZATION ALGORITHM. Electrical Engineering & Electromechanics, (2), 47–54. https://doi.org/10.20998/2074-272X.2019.2.07

Issue

No. 2 (2019)

Section

Power Stations, Grids and Systems

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Copyright (c) 2019 Arif Bourzami, Mohammed Amroune, Tarek Bouktir

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